Text- and Content-based Approaches to Image Retrieval for the ImageCLEF 2009 Medical Retrieval Track

This article describes the participation of the Image and Text Integration (ITI) group from the United States National Library of Medicine (NLM) in the ImageCLEF 2009 medical retrieval track. Our methods encompass a variety of techniques relating to document summarization and textand content-based image retrieval. Our text-based approach utilizes the Unified Medical Language System (UMLS) synonymy of concepts identified in information requests and image-related text to retrieve semantically relevant images. Our content-based approaches utilize similarity metrics based on computed “visual concepts” to identify visually similar images. In this article we present an overview of these approaches, discuss our experiences combining them into multimodal retrieval strategies, and describe our submitted runs and results.